Traps in Multisource Heterogeneous Big Data Processing

Abstract

The importance of big data values and application efforts has reached a universal consensus in most fields. While because of the model difference of data storage, computing and analysis, the big data processing performance and big data values show greatly uneven in different scenarios. In this paper, we analyze the traps which may greatly impact big data processing results, and give our suggestions to solve these problems for the multisource and heterogeneous characteristics of big data.